Adaptive Filters for Continuous Queries over Distributed Data Streams

Abstract

We consider an environment where distributed data sources continuously stream updates to a centralized processor that monitors continuous queries over the distributed data. Significant communication overhead is incurred in the presence of rapid update streams, and we propose a new technique for reducing the overhead. Users register continuous queries with precision requirements at the central stream processor, which installs filters at remote data sources. The filters adapt to changing conditions to minimize stream rates while guaranteeing that all continuous queries still receive the updates necessary to provide answers of adequate precision at all times. Our approach enables applications to trade precision for communication overhead at a fine granularity by individually adjusting the precision constraints of continuous queries over streams in a multi-query workload. Through experiments performed on synthetic data simulations and a real network monitoring implementation, we demonstrate the effectiveness of our approach in achieving low communication overhead compared with alternate approaches.

Available Versions of this Item

• Approximate Caching for Continuous Queries over Distributed Data Sources. (deposited 17 Feb 2002 16:00)
  • Adaptive Filters for Continuous Queries over Distributed Data Streams. (deposited 14 Nov 2002 16:00) [Currently Displayed]
    • Adaptive Filters for Continuous Queries over Distributed Data Streams. (deposited 12 Feb 2003 16:00)